An attention-based effective neural model for drug-drug interactions extraction
作者: Wei ZhengHongfei LinLing LuoZhehuan ZhaoZhengguang LiYijia ZhangZhihao YangJian Wang
作者单位: 1College of Computer Science and Technology, Dalian University of Technology
2College of Software, Dalian JiaoTong University
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Journal
DOI: 10.1186/s12859-017-1855-x
关键词: AttentionRecurrent neural networkLong short-term memoryDrug-drug interactionsText mining
英文摘要: Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory.
原始语种摘要: Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory.
全文获取路径: Springer  (合作)
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来源刊物:
影响因子:3.024 (2012)

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关键词翻译
关键词翻译
  • neural 神经系统的
  • unexpected 突然的
  • model 模型
  • unsatisfactory 不满意的
  • short 短的
  • often 往往
  • issue 
  • based 基于
  • mining 矿业
  • safety 安全